Controllo dell'atto di prensione: coinvolgimento dell'area V6A nell'orientamento del polso

Prehension in an act of coordinated reaching and grasping. The reaching component is concerned with bringing the hand to object to be grasped (transport phase); the grasping component refers to the shaping of the hand according to the object features (grasping phase) (Jeannerod, 1981). Reaching and grasping involve different muscles, proximal and distal muscles respectively, and are controlled by different parietofrontal circuit (Jeannerod et al., 1995): a medial circuit, involving area of superior parietal lobule and dorsal premotor area 6 (PMd) (dorsomedial visual stream), is mainly concerned with reaching; a lateral circuit, involving the inferior parietal lobule and ventral premotor area 6 (PMv) (dorsolateral visual stream), with grasping. Area V6A is located in the caudalmost part of the superior parietal lobule, so it belongs to the dorsomedial visual stream; it contains neurons sensitive to visual stimuli (Galletti et al. 1993, 1996, 1999) as well as cells sensitive to the direction of gaze (Galletti et al. 1995) and cells showing saccade-related activity (Nakamura et al. 1999; Kutz et al. 2003). Area V6A contains also arm-reaching neurons likely involved in the control of the direction of the arm during movements towards objects in the peripersonal space (Galletti et al. 1997; Fattori et al. 2001). The present results confirm this finding and demonstrate that during the reach-to-grasp the V6A neurons are also modulated by the orientation of the wrist. Experiments were approved by the Bioethical Committee of the University of Bologna and were performed in accordance with National laws on care and use of laboratory animals and with the European Communities Council Directive of 24th November 1986 (86/609/EEC), recently revised by the Council of Europe guidelines (Appendix A of Convention ETS 123). Experiments were performed in two awake Macaca fascicularis. Each monkey was trained to sit in a primate chair with the head restrained to perform reaching and grasping arm movements in complete darkness while gazing a small fixation point. The object to be grasped was a handle that could have different orientation. We recorded neural activity from 163 neurons of the anterior parietal sulcus; 116/163 (71%) neurons were modulated by the reach-to-grasp task during the execution of the forward movements toward the target (epoch MOV), 111/163 (68%) during the pulling of the handle (epoch HOLD) and 102/163 during the execution of backward movements (epoch M2) (t_test, p ≤ 0.05). About the 45% of the tested cells turned out to be sensitive to the orientation of the handle (one way ANOVA, p ≤ 0.05). To study how the distal components of the movement, such as the hand preshaping during the reaching of the handle, could influence the neuronal discharge, we compared the neuronal activity during the reaching movements towards the same spatial location in reach-to-point and reach-to-grasp tasks. Both tasks required proximal arm movements; only the reach-to-grasp task required distal movements to orient the wrist and to shape the hand to grasp the handle. The 56% of V6A cells showed significant differences in the neural discharge (one way ANOVA, p ≤ 0.05) between the reach-to-point and the reach-to-grasp tasks during MOV, 54% during HOLD and 52% during M2. These data show that reaching and grasping are processed by the same population of neurons, providing evidence that the coordination of reaching and grasping takes place much earlier than previously thought, i.e., in the parieto-occipital cortex. The data here reported are in agreement with results of lesions to the medial posterior parietal cortex in both monkeys and humans, and with recent imaging data in humans, all of them indicating a functional coupling in the control of reaching and grasping by the medial parietofrontal circuit.

Self-organising coordination systems

Many research fields are pushing the engineering of large-scale, mobile, and open systems towards the adoption of techniques inspired by self-organisation: pervasive computing, but also distributed artificial intelligence, multi-agent systems, social networks, peer-topeer and grid architectures exploit adaptive techniques to make global system properties emerge in spite of the unpredictability of interactions and behaviour. Such a trend is visible also in coordination models and languages, whenever a coordination infrastructure needs to cope with managing interactions in highly dynamic and unpredictable environments. As a consequence, self-organisation can be regarded as a feasible metaphor to define a radically new conceptual coordination framework. The resulting framework defines a novel coordination paradigm, called self-organising coordination, based on the idea of spreading coordination media over the network, and charge them with services to manage interactions based on local criteria, resulting in the emergence of desired and fruitful global coordination properties of the system. Features like topology, locality, time-reactiveness, and stochastic behaviour play a key role in both the definition of such a conceptual framework and the consequent development of self-organising coordination services. According to this framework, the thesis presents several self-organising coordination techniques developed during the PhD course, mainly concerning data distribution in tuplespace-based coordination systems. Some of these techniques have been also implemented in ReSpecT, a coordination language for tuple spaces, based on logic tuples and reactions to events occurring in a tuple space. In addition, the key role played by simulation and formal verification has been investigated, leading to analysing how automatic verification techniques like probabilistic model checking can be exploited in order to formally prove the emergence of desired behaviours when dealing with coordination approaches based on self-organisation. To this end, a concrete case study is presented and discussed.

Semantic coordination through programmable Tuple spaces

Two of the main features of today complex software systems like pervasive computing systems and Internet-based applications are distribution and openness. Distribution revolves around three orthogonal dimensions: (i) distribution of control|systems are characterised by several independent computational entities and devices, each representing an autonomous and proactive locus of control; (ii) spatial distribution|entities and devices are physically distributed and connected in a global (such as the Internet) or local network; and (iii) temporal distribution|interacting system components come and go over time, and are not required to be available for interaction at the same time. Openness deals with the heterogeneity and dynamism of system components: complex computational systems are open to the integration of diverse components, heterogeneous in terms of architecture and technology, and are dynamic since they allow components to be updated, added, or removed while the system is running. The engineering of open and distributed computational systems mandates for the adoption of a software infrastructure whose underlying model and technology could provide the required level of uncoupling among system components. This is the main motivation behind current research trends in the area of coordination middleware to exploit tuple-based coordination models in the engineering of complex software systems, since they intrinsically provide coordinated components with communication uncoupling and further details in the references therein. An additional daunting challenge for tuple-based models comes from knowledge-intensive application scenarios, namely, scenarios where most of the activities are based on knowledge in some form|and where knowledge becomes the prominent means by which systems get coordinated. Handling knowledge in tuple-based systems induces problems in terms of syntax - e.g., two tuples containing the same data may not match due to differences in the tuple structure - and (mostly) of semantics|e.g., two tuples representing the same information may not match based on a dierent syntax adopted. Till now, the problem has been faced by exploiting tuple-based coordination within a middleware for knowledge intensive environments: e.g., experiments with tuple-based coordination within a Semantic Web middleware (surveys analogous approaches). However, they appear to be designed to tackle the design of coordination for specic application contexts like Semantic Web and Semantic Web Services, and they result in a rather involved extension of the tuple space model. The main goal of this thesis was to conceive a more general approach to semantic coordination. In particular, it was developed the model and technology of semantic tuple centres. It is adopted the tuple centre model as main coordination abstraction to manage system interactions. A tuple centre can be seen as a programmable tuple space, i.e. an extension of a Linda tuple space, where the behaviour of the tuple space can be programmed so as to react to interaction events. By encapsulating coordination laws within coordination media, tuple centres promote coordination uncoupling among coordinated components. Then, the tuple centre model was semantically enriched: a main design choice in this work was to try not to completely redesign the existing syntactic tuple space model, but rather provide a smooth extension that { although supporting semantic reasoning { keep the simplicity of tuple and tuple matching as easier as possible. By encapsulating the semantic representation of the domain of discourse within coordination media, semantic tuple centres promote semantic uncoupling among coordinated components. The main contributions of the thesis are: (i) the design of the semantic tuple centre model; (ii) the implementation and evaluation of the model based on an existent coordination infrastructure; (iii) a view of the application scenarios in which semantic tuple centres seem to be suitable as coordination media.

Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

Design and Control of Robotic Hands

The application of dexterous robotic hands out of research laboratories has been limited by the intrinsic complexity that these devices present. This is directly reflected as an economically unreasonable cost and a low overall reliability. Within the research reported in this thesis it is shown how the problem of complexity in the design of robotic hands can be tackled, taking advantage of modern technologies (i.e. rapid prototyping), leading to innovative concepts for the design of the mechanical structure, the actuation and sensory systems. The solutions adopted drastically reduce the prototyping and production costs and increase the reliability, reducing the number of parts required and averaging their single reliability factors. In order to get guidelines for the design process, the problem of robotic grasp and manipulation by a dual arm/hand system has been reviewed. In this way, the requirements that should be fulfilled at hardware level to guarantee successful execution of the task has been highlighted. The contribution of this research from the manipulation planning side focuses on the redundancy resolution that arise in the execution of the task in a dexterous arm/hand system. In literature the problem of coordination of arm and hand during manipulation of an object has been widely analyzed in theory but often experimentally demonstrated in simplified robotic setup. Our aim is to cover the lack in the study of this topic and experimentally evaluate it in a complex system as a anthropomorphic arm hand system.